23 citations · 61 across the 6 of their papers we have counts for
6 papers
Finding the Weakest Link: Adversarial Attack against Multi-Agent Communications
Maxwell Standen, Junae Kim, Claudia Szabo
Multi-agent systems rely on communication for information sharing and action coordination, which exposes a vulnerability to attacks. We investigate single-victim communication pert…
On Autonomous Agents in a Cyber Defence Environment
Mitchell Kiely, David Bowman, Maxwell Standen +1
Autonomous Cyber Defence is required to respond to high-tempo cyber-attacks. To facilitate the research in this challenging area, we explore the utility of the autonomous cyber ope…
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning
Maxwell Standen, Junae Kim, Claudia Szabo
Multi-Agent Reinforcement Learning (MARL) is vulnerable to Adversarial Machine Learning (AML) attacks and needs adequate defences before it can be used in real world applications.…
Deep hierarchical reinforcement agents for automated penetration testing
Khuong Tran, Ashlesha Akella, Maxwell Standen +4
Penetration testing the organised attack of a computer system in order to test existing defences has been used extensively to evaluate network security. This is a time consuming pr…
CybORG: A Gym for the Development of Autonomous Cyber Agents
Maxwell Standen, Martin Lucas, David Bowman +3
Autonomous Cyber Operations (ACO) involves the development of blue team (defender) and red team (attacker) decision-making agents in adversarial scenarios. To support the applicati…
CybORG: An Autonomous Cyber Operations Research Gym
Callum Baillie, Maxwell Standen, Jonathon Schwartz +3
Autonomous Cyber Operations (ACO) involves the consideration of blue team (defender) and red team (attacker) decision-making models in adversarial scenarios. To support the applica…